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OpenRLHF

Appears in 4 awesome lists

an easy-to-use, high-performance open-source RLHF framework built on Ray, vLLM, ZeRO-3 and HuggingFace Transformers, designed to make RLHF training simple and accessible

Open github.comopenrlhf/openrlhf

Found in these lists

When LLM Agents Meet Reinforcement Learning

Section: Base Framework · OpenRLHF

FreshScore 81

Awesome local LLM

Section: Training and Fine-tuning · an easy-to-use, high-performance open-source RLHF framework built on Ray, vLLM, ZeRO-3 and HuggingFace Transformers, designed to make RLHF training simple and accessible

FreshScore 87

Awesome Open Source AI

Section: 7. Training & Fine-tuning Ecosystem · Easy-to-use, scalable RLHF framework based on Ray. Supports PPO, GRPO, REINFORCE++, DAPO with vLLM integration and async training. Apache 2.0 licensed.

FreshScore 89

Awesome Production Machine Learning

Section: Industry Strength Reinforcement Learning · OpenRLHF is an open-source framework for reinforcement learning from human feedback (RLHF).

FreshScore 92

Colossal-AI

(from Hpcaitech) - A Unified Deep Learning System for Large-Scale Parallel Training (1D, 2D, 2.5D, 3D and sequence parallelism, and ZeRO protocol).

In 14 listsDetails

Ray

A fast and simple framework for building and running distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library. ray.io

In 13 listsDetails

FastChat

Open platform for training, serving, and evaluating large language model chatbots. Powers Chatbot Arena (lmarena.ai) serving 10M+ requests for 70+ LLMs. Includes training code for Vicuna, MT-Bench evaluation, and distributed multi-model serving with OpenAI-compatible APIs. Apache 2.0 licensed.

In 12 listsDetails

unsloth

Fine-tuning & Reinforcement Learning for LLMs. Train OpenAI gpt-oss, DeepSeek-R1, Qwen3, Gemma 3, TTS 2x faster with 70% less VRAM.

In 8 listsDetails

TRL

Train transformer language models with reinforcement learning.

In 8 listsDetails

PEFT

Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of pre-trained language models (PLMs) to various downstream applications without fine-tuning all the model's parameters.

In 7 listsDetails

LeRobot

Making AI for robotics more accessible with end-to-end learning. State-of-the-art approaches for imitation learning and reinforcement learning with pretrained models, datasets, and simulated environments. Apache 2.0 licensed.

In 6 listsDetails

Ludwig

Low-code framework for building custom LLMs and deep neural networks. Declarative YAML configuration for training state-of-the-art models with PEFT/LoRA, 4-bit quantization, distributed training via Hugging Face Accelerate, and native Kubernetes support. Linux Foundation AI project. Apache 2.0…

In 6 listsDetails